We next verify the segmentation via a series of quantitative experiments, whose results are reported in Table REF . We compare our method to baselines starting with random segmentation assignment of pixels using the same number of segments as our method (to give an uninformed baseline for each metric). Unsurprisingly, this random method underperforms our method at ensuring segments are relatively homogeneous within and heterogeneous between segments. We then compare to two additional segmentation methods that, like ours, are unsupervised. We first compare to a Otsu's method-thresholded, peak-finding watershed algorithm [1]} and a graph-based image segmentation method we refer to as Felzenszwalb [2]}. Results are reported as a mean and standard deviation across three independent trials.
